Abstract

Autonomous mobile robots are taking on more tasks in warehouses, speeding up operations and reducing accidents that claim many lives each year. This work proposes a dynamic path planning algorithm, based on A* search method for large autonomous mobile robots such as forklifts, and generates an optimized, time-efficient path. Simulation results of the proposed turn and orientation sensitive A* algorithm show that it has a 94% success rate of computing a better or similar path compared to that of default A*. The generated paths are smoother, have fewer turns, resulting in faster execution of tasks. The method also robustly handles unexpected obstacles in the path.

Library of Congress Subject Headings

Autonomous robots--Programming; Autonomous robots--Dynamics; Materials handling--Automation; Automated vehicles--Data processing

Publication Date

5-2020

Document Type

Thesis

Student Type

Graduate

Degree Name

Electrical Engineering (MS)

Department, Program, or Center

Electrical Engineering (KGCOE)

Advisor

Ferat Sahin

Advisor/Committee Member

Clark Hochgraf

Advisor/Committee Member

Jamison Heard

Campus

RIT – Main Campus

Plan Codes

EEEE-MS

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